It is a common experience among photographers that a subject of a scene is much darker than the background. For example, in outdoor photography, a subject may be situated against a bright sky, beach, or snow. In indoor photography, the subject may be situated in a relatively dark room having bright windows, ceiling lights, or other bright objects. For scenes having these characteristics, the photographer may manually adjust exposure settings so that the subject of the image is brightly lit, allowing bright background areas to become over-exposed. These exposure settings generally include shutter speed and aperture (f-stop) setting. For film-based cameras, the appropriate exposure settings will vary with the film speed. For digital cameras, the exposure setting can also include a sensitivity (ISO) value, sometimes referred to as gain. The appropriate shutter speed and aperture setting also has implications for depth-of-field. The challenge of correctly identifying optimum exposure settings for a particular scene is daunting to many photographers, novice and professional alike.
In an attempt to simplify exposure settings for novice photographers, many cameras have various automatic exposure settings which cause the camera to select an appropriate shutter speed for a particular aperture, an appropriate aperture for a particular shutter speed, or fully automatic exposure in which the camera selects an appropriate shutter speed and aperture. To achieve any automatic exposure setting, however, the camera must have some way of detecting the brightness of the image prior to taking the picture so that the exposure is adjusted appropriately for the scene.
Camera manufacturers have developed many mechanisms for automatically selecting exposure settings for particular scenes. In traditional film-based photography, the simplest auto-exposure cameras have a light meter that reads an overall amount of light in the scene as whole, and adjusts the exposure setting according to the level of light. Unfortunately, where the image contains an excessive amount of light in the background of a scene, the automatic exposure setting will result in the subject being too darkly lit, and may appear in shadow or even silhouetted in extreme cases. To reduce the effects of backlighting, some film-based cameras identify brightness levels at different regions of an image and give greater weight to the brightness at the center of the image. The result of these systems varies depending on whether the subject is centrally located when the picture is taken. In another approach, “spot metering” is performed at a central portion of the image frame. The photographer is required to align the subject with the central spot, store the exposure details for the subject, compose the picture, possibly arranging the subject off to one side, and finally take the picture. While this process generally results in a properly balanced image, it significantly increases the complexity beyond the simple “point and shoot” operation that many photographers demand.
In digital photography, it is common for a camera to determine exposure settings by utilizing the image sensor itself either during the exposure period or immediately before the exposure period. Such information may be referred to as “pre-image data” and may be used to estimate appropriate automatic exposure settings. Prior art cameras employ various algorithms using pre-image data to calculate an optimum exposure estimate. For example, the image area may be divided into a number of segments, with the average luminance calculated or estimated for each segment, with centrally-positioned segments being weighted more than peripheral segments. In this way, these advanced digital cameras mimic the functionality of existing film-based cameras. However, the algorithms used to determine an optimum exposure estimate can be complex, requiring a number of averages to be calculated, which is burdensome for small hand-held cameras or low-power devices such as cell phones that incorporate imaging functionality and have limited processing power.
Therefore, there is an unmet need for a simplified optimum exposure estimating device or method to compensate for bright background regions of a scene.